Ingest
Turn every document, archive, and internal site into searchable, source-linked knowledge.
Ingest a decade of circulars and procedures. Ask a question. Get page-numbered answers.
Banking, insurance, operations, compliance — enterprise AI deployed where your data already lives. On-premise, air-gapped, or in your own cloud. Nothing ever crosses your perimeter.
In private preview with selected financial institutions across EMEA.
Deeplinq is the AI layer for enterprises that can't send their data to a vendor's cloud. We deploy inside your perimeter, connect to your legacy systems, and put governed agents in every team's hands — without a data science team.
What deeplinq does
Turn every document, archive, and internal site into searchable, source-linked knowledge.
Ingest a decade of circulars and procedures. Ask a question. Get page-numbered answers.
Read from and write to the systems your business already runs on — no rip-and-replace.
Query SAP, update Salesforce, trigger a core-banking workflow — from a single conversation.
Run every leading LLM behind one governed layer. Switch models as your needs evolve.
Anthropic for legal summaries. Mistral on-prem for conversations. Your model for risk scoring.
Ship AI agents scoped to a team, a use case, a compliance context — in days, not quarters.
An onboarding agent for retail banking. A circular-research agent for compliance. Each with its own guardrails.
Every prompt logged. Every answer traceable. Every access role-bound.
A full audit trail exportable for regulators. Role-based access controls. Topic guardrails enforced by policy.
What it changes
Regulated teams spend most of their week finding information, reconciling across systems, and producing paperwork. Deeplinq lets them spend it on judgment.
From four systems to brief a client to one conversation that assembles the client view.
From reading 200 pages for one regulator question to a sourced answer with circular references in seconds.
From hours of manual reconciliation to agents that draft, check, and route for approval.
From waiting for the quarterly dashboard to asking the business a question and getting the answer today.
Outcomes based on design-partner pilots currently underway. Published case studies available as partners authorize disclosure.
Why deeplinq exists
2011
Brams, Google GSA enterprise partner, EMEA
2015
Bridge, contextual business views across indexed data (direct ancestor of deeplinq)
2023
Deeplinq spun off as independent AI middleware
Deeplinq began in 2011, when an EMEA team joined Google's Enterprise Search Appliance partners. Gulf deployments exposed the limits of rigid search — and the Bridge module that emerged is the direct ancestor of deeplinq. In 2023, deeplinq spun off as AI middleware for regulated enterprises.
Deeplinq's team draws on fifteen years of enterprise data expertise, with three years of dedicated focus on enterprise AI middleware — engineered for the sovereign AI era.
Tech entrepreneur who built and scaled companies while leading large-scale IT programmes on legacy-heavy environments. Anticipated each major shift — internet, cloud, AI — with strategic vision and hands-on execution.
Built for the teams that carry the risk
One platform. Team-scoped deployments. Your team defines the workflow; deeplinq provides connectors, orchestration, and audit trail. No shared context between agents unless authorized.
Client 360 data plane from the systems you already run. Meeting prep in seconds.
Regulatory research across circulars. Control-check workflows your team defines. Sourced answers.
Infrastructure for signal-detection workflows. Full audit trail on every decision.
Reporting, reconciliation, document processing — drafted by agents, validated by your team.
Ask the business in natural language. Answers grounded in live data.
Open APIs. MCP and A2A. Your models behind our orchestration. No lock-in.
No model lock-in
Deeplinq runs against the model that fits your sovereignty and compliance posture. Cloud APIs for non-sensitive workloads. Open-weights models for on-premise or air-gapped deployments. Switch per use case, per team, or per policy. When a better model ships, you get to adopt it. Not us.
Supported models
Cloud APIs (with data residency)
Open-weights (self-hosted)
Including your own fine-tuned or on-premise models. Additional providers on request.
Open protocols
Deployed where you need it
Install on your own servers. Full control over hardware, networking, data.
For: institutions with mature infrastructure and strict residency.
Zero outbound network dependency. For environments where telemetry is too much.
For: defense-adjacent, classified, offline industrial.
Deploy into AWS, Azure, Google Cloud, or sovereign cloud. You own infrastructure, we provide platform.
For: cloud-committed enterprises with data-residency control.
Multi-tenant deeplinq. EU-hosted by default. No data leaves the region you select.
For: innovation teams, proofs of concept, non-regulated workloads.
No proprietary hardware. No vendor lock-in.
Deeplinq installs on your specified infrastructure — we adapt to what you have.
12 weeks, 4 phases, co-constructed. From customer-side preparation to in-production operations, every phase is mapped — including the prerequisites on your side.
Built for regulated environments
Post-Schrems II, "EU region" ≠ "EU sovereignty". Regulators tighten, boards ask harder questions, AI vendors still ship prompts through infrastructure they don't fully control. Our architecture is engineered against GDPR, EU AI Act, DORA, MiFID II, Solvency II, FINMA, ACPR/CNIL, and ISO 27001 / SOC 2 — audit-ready by default.
Deeplinq runs inside your environment. Prompts, documents, connections, inference stay where your legal team said. No exfiltration by design. Not by policy. By architecture.
Deployments respect jurisdiction. EU stays EU. UK stays UK. DACH stays DACH.
Architected around EU AI Act transparency, logging, and risk-classification. Audit-ready from day one.
Queries never reach a vendor's cloud. Model calls on-premise. Your data is yours, end to end.
Beyond banking
Our first deployments are in banking because that is where sovereignty, compliance, and legacy complexity are hardest. What works in a bank works in an insurer, an industrial operator, a public institution — with their own constraints and their own data that cannot move.
We are building deeplinq into the category platform for enterprise AI that runs inside the perimeter — across regulated industries, across regions, with our partner ecosystem. One platform. Every regulated team. Your infrastructure.
Deeplinq is currently working with a small number of design partners across EMEA financial institutions. If you're responsible for AI strategy, data governance, or a regulated workflow — we'd like to hear from you.
25-minute conversation. No deck. We want to understand your constraints first.